Contribution of hypoxia to Alzheimer's disease: is HIF-1α a mediator of neurodegeneration?

The mammalian brain is extremely sensitive to alterations in cellular homeostasis as a result of environmental or physiological insults. In particular, hypoxic/ischemic challenges (i.e. reduced oxygen and/or glucose delivery) cause severe and detrimental alterations in brain function and can trigger neuronal cell death within minutes. Unfortunately, as we age, oxygen delivery to cells and tissues is impaired, thereby increasing the susceptibility of neurons to damage. Thus, hypoxic (neuronal) adaptation is significantly compromised during aging. Many neurological diseases, such as stroke, Alzheimer's disease (AD), Parkinson's disease and diabetes, are characterized by hypoxia, a state that is believed to only exacerbate disease progression. However, the contribution of hypoxia and hypoxia-mediated pathways to neurodegeneration remains unclear. This review discusses current evidence on the contribution of oxygen deprivation to AD, with an emphasis on hypoxia inducible transcription factor-1 (HIF-1)-mediated pathways and the association of AD with the cytoskeleton regulator cyclin-dependent kinase 5. (Part of a multi-author review.

Multimodality in Pervasive Environment

Future pervasive environments are expected to immerse users in a consistent world of probes, sensors and actuators. Multimodal interfaces combined with social computing interactions and high-performance networking can foster a new generation of pervasive environments. However, much work is still needed to harness the full potential of multimodal interaction. In this paper we discuss some short-term research goals, including advanced techniques for joining and correlating multiple data flows, each with its own approximations and uncertainty models. Also, we discuss some longer term objectives, like providing users with a mental model of their own multimodal "aura", enabling them to collaborate with the network infrastructure toward inter-modal correlation of multimodal inputs, much in the same way as the human brain extracts a single self-conscious experience from multiple sensorial data flows

Is there a d.c. Josephson Effect in Bilayer Quantum Hall Systems?

We argue on the basis of phenomenological and microscopic considerations that there is no d.c. Josephson effect in ordered bilayer quantum Hall systems, even at T=0. Instead the tunnel conductance is strongly enhanced, approaching a finite value proportional to the square of the order parameter as the interlayer tunneling amplitude vanishes.Comment: 5 pages, 2 figure

CSC-GAN:Cycle and Semantic Consistency for Dataset Augmentation

Image-to-image translation is a computer vision problem where a task learns a mapping from a source domain A to a target domain B using a training set. However, this translation is not always accurate, and during the translation process, relevant semantic information can deteriorate. To handle this problem, we propose a new cycle-consistent, adversarially trained image-to-image translation with a loss function that is constrained by semantic segmentation. This formulation encourages the model to preserve semantic information during the translation process. For this purpose, our loss function evaluates the accuracy of the synthetically generated image against a semantic segmentation model, previously trained. Reported results show that our proposed method can significantly increase the level of details in the synthetic images. We further demonstrate our method’s effectiveness by applying it as a dataset augmentation technique, for a minimal dataset, showing that it can improve the semantic segmentation accuracy

Irreversibility in a simple reversible model

This paper studies a parametrized family of familiar generalized baker maps, viewed as simple models of time-reversible evolution. Mapping the unit square onto itself, the maps are partly contracting and partly expanding, but they preserve the global measure of the definition domain. They possess periodic orbits of any period, and all maps of the set have attractors with well defined structure. The explicit construction of the attractors is described and their structure is studied in detail. There is a precise sense in which one can speak about absolute age of a state, regardless of whether the latter is applied to a single point, a set of points, or a distribution function. One can then view the whole trajectory as a set of past, present and future states. This viewpoint is then applied to show that it is impossible to define a priori states with very large "negative age". Such states can be defined only a posteriori. This gives precise sense to irreversibility -- or the "arrow of time" -- in these time-reversible maps, and is suggested as an explanation of the second law of thermodynamics also for some realistic physical systems.Comment: 15 pages, 12 Postscript figure

Parallel comparison of Illumina RNA-Seq and Affymetrix microarray platforms on transcriptomic profiles generated from 5-aza-deoxy-cytidine treated HT-29 colon cancer cells and simulated datasets

BACKGROUND: High throughput parallel sequencing, RNA-Seq, has recently emerged as an appealing alternative to microarray in identifying differentially expressed genes (DEG) between biological groups. However, there still exists considerable discrepancy on gene expression measurements and DEG results between the two platforms. The objective of this study was to compare parallel paired-end RNA-Seq and microarray data generated on 5-azadeoxy-cytidine (5-Aza) treated HT-29 colon cancer cells with an additional simulation study. METHODS: We first performed general correlation analysis comparing gene expression profiles on both platforms. An Errors-In-Variables (EIV) regression model was subsequently applied to assess proportional and fixed biases between the two technologies. Then several existing algorithms, designed for DEG identification in RNA-Seq and microarray data, were applied to compare the cross-platform overlaps with respect to DEG lists, which were further validated using qRT-PCR assays on selected genes. Functional analyses were subsequently conducted using Ingenuity Pathway Analysis (IPA). RESULTS: Pearson and Spearman correlation coefficients between the RNA-Seq and microarray data each exceeded 0.80, with 66%~68% overlap of genes on both platforms. The EIV regression model indicated the existence of both fixed and proportional biases between the two platforms. The DESeq and baySeq algorithms (RNA-Seq) and the SAM and eBayes algorithms (microarray) achieved the highest cross-platform overlap rate in DEG results from both experimental and simulated datasets. DESeq method exhibited a better control on the false discovery rate than baySeq on the simulated dataset although it performed slightly inferior to baySeq in the sensitivity test. RNA-Seq and qRT-PCR, but not microarray data, confirmed the expected reversal of SPARC gene suppression after treating HT-29 cells with 5-Aza. Thirty-three IPA canonical pathways were identified by both microarray and RNA-Seq data, 152 pathways by RNA-Seq data only, and none by microarray data only. CONCLUSIONS: These results suggest that RNA-Seq has advantages over microarray in identification of DEGs with the most consistent results generated from DESeq and SAM methods. The EIV regression model reveals both fixed and proportional biases between RNA-Seq and microarray. This may explain in part the lower cross-platform overlap in DEG lists compared to those in detectable genes

JNK plays a key role in tau hyperphosphorylation in Alzheimer's disease models

Alzheimer's disease (AD) is a major clinical concern, and the search for new molecules to combat disease progression remains important. One of the major hallmarks in AD pathogenesis is the hyperphosphorylation of tau and subsequent formation of neurofibrillary tangles. Several kinases are involved in this process. Amongst them, c-Jun N-terminal kinases (JNKs) are activated in AD brains and are also associated with the development of amyloid plaques. This study was designed to investigate the contribution of JNK in tau hyperphosphorylation and whether it may represent a potential therapeutic target for the fight against AD. The specific inhibition of JNK by the cell permeable peptide D-JNKI-1 led to a reduction of p-tau at S202/T205 and S422, two established target sites of JNK, in rat neuronal cultures and in human fibroblasts cultures. Similarly, D-JNKI-1 reduced p-tau at S202/T205 in an in vivo model of AD (TgCRND8 mice). Our findings support the fundamental role of JNK in the regulation of tau hyperphosphorylation and subsequently in AD pathogenesis

JNK Contributes to Hif-1α Regulation in Hypoxic Neurons

Hypoxia is an established factor of neurodegeneration. Nowadays, attention is directed at understanding how alterations in the expression of stress-related signaling proteins contribute to age dependent neuronal vulnerability to injury. The purpose of this study was to investigate how Hif-1alpha, a major neuroprotective factor, and JNK signaling, a key pathway in neurodegeneration, relate to hypoxic injury in young (6DIV) and adult (12DIV) neurons. We could show that in young neurons as compared to mature ones, the protective factor Hif-1alpha is more induced while the stress protein phospho-JNK displays lower basal levels. Indeed, changes in the expression levels of these proteins correlated with increased vulnerability of adult neurons to hypoxic injury. Furthermore, we describe for the first time that treatment with the D-JNKI1, a JNK-inhibiting peptide, rescues adult hypoxic neurons from death and contributes to Hif-1alpha upregulation, probably via a direct interaction with the Hif-1alpha protei

Two populations of X-ray pulsars produced by two types of supernovae

Two types of supernova are thought to produce the overwhelming majority of neutron stars in the Universe. The first type, iron-core collapse supernovae, occurs when a high-mass star develops a degenerate iron core that exceeds the Chandrasekhar limit. The second type, electron-capture supernovae, is associated with the collapse of a lower-mass oxygen-neon-magnesium core as it loses pressure support owing to the sudden capture of electrons by neon and/or magnesium nuclei. It has hitherto been impossible to identify the two distinct families of neutron stars produced in these formation channels. Here we report that a large, well-known class of neutron-star-hosting X-ray pulsars is actually composed of two distinct sub-populations with different characteristic spin periods, orbital periods and orbital eccentricities. This class, the Be/X-ray binaries, contains neutron stars that accrete material from a more massive companion star. The two sub-populations are most probably associated with the two distinct types of neutron-star-forming supernovae, with electron-capture supernovae preferentially producing system with short spin period, short orbital periods and low eccentricity. Intriguingly, the split between the two sub-populations is clearest in the distribution of the logarithm of spin period, a result that had not been predicted and which still remains to be explaine